Title: Effects of home confinement on mental health and lifestyle behaviours during the

COVID-19 outbreak: Insight from the "ECLB-COVID19" multi countries survey

Original article

ECLB-COVID19 Consortium

Achraf Ammar1 (0000-0003-0347-8053), Khaled Trabelsi2, Michael Brach3, Hamdi Chtourou2, Omar

Boukhris2, Liwa Masmoudi2, Bassem Bouaziz4, Ellen Bentlage3, Daniella How3, Mona Ahmed3, Patrick

Mueller5, Notger Mueller5, Asma Aloui2, Omar Hammouda2, Laisa Liane Paineiras-Domingos6, Annemarie

Braakman-jansen7, Christian Wrede7, Sophia Bastoni8, Carlos Soares Pernambuco9, Leonardo Mataruna10,

Morteza Taheri11, Khadijeh Irandoust11, Aïmen Khacharem12, Nicola L Bragazzi13, Karim Chamari14, Jordan

M Glenn15, Nicholas T Bott16, Faiez Gargouri4, Lotfi Chaari17, Hadj Batatia17, Gamal Mohamed Ali18, Osama

Abdelkarim19, Mohamed Jarraya2, Kais El Abed2, Nizar Souissi20, Lisette Van Gemert-Pijnen7, Bryan L

Riemann21, Laurel Riemann22, Wassim Moalla2, Jonathan Gómez-Raja23, Monique Epstein24, Robbert

Sanderman25, Sebastian Schulz26, Achim Jerg26, Ramzi Al-Horani27, Taysir Mansi28, Mohamed Jmail29,

Fernando Barbosa30, Fernando Santos31, Boštjan Šimunič32, Rado Pišot32, Donald Cowan33, Andrea Gaggioli8,

Stephen J Bailey34, Jürgen Steinacker26, Tarak Driss35, Anita Hoekelmann1

1 Institute of Sport Science, Otto-von-Guericke University, 39106, Magdeburg, Germany 2 High Institute of Sport and Physical Education of Sfax, 3000, Sfax, Tunisia 3Institute of Sport and Exercise Sciences, Münster, Germany Michael Brach 4 Higher Institute of Computer Science and Multimedia of Sfax, 3000, Sfax, Tunisia 5 Research Group Neuroprotection, German Center for Neurodegenerative Diseases (DZNE), Magdeburg,

Germany 6 Laboratório de Vibrações Mecânicas e Práticas Integrativas, Departamento de Biofísica e Biometria,

Instituto de Biologia Roberto Alcântara Gomes e Policlínica Piquet Carneiro, Universidade do Estado do Rio

de Janeiro, Rio de Janeiro, RJ, Brazil 7 University of Twente, the Netherlands Région de Enschede, Netherland 8 Catholic University of the Sacred Heart I UNICATT, Milano, Italy 9 Laboratório de Biociências da Motricidade Humana (LABIMH) da Universidade Federal do Estado do Rio

de Janeiro (UNIRIO) – Rio de Janeiro/RJ – Brasil 10 College of Business Administration, American University in the Emirates, Dubai, UAE 11 Imam Khomeini International University, Qazvin, Iran 12 UVHC, DeVisu, Valenciennes, France; LIRTES - EA 7313. Université Paris Est Créteil Val de Marne 13 Department of Health Sciences (DISSAL), Postgraduate School of Public Health, University of Genoa,

Genoa 16132, Italy 14 Department of Research and Education / Aspetar, Qatar 15 Exercise Science Research Center, Department of Health, Human Performance and Recreation, University

of Arkansas, AR 72701, Fayetteville, USA 16 Clinical Excellence Research Center, Department of Medicine, Stanford University School of Medicine,

CA 94305, Stanford, USA 17 University of Toulouse, IRIT - INP-ENSEEIHT, France 18 Faculty of Physical Education, Assiut University, Assiut 71515, Egypt 19 Karlsruher Institut für Technologie, Karlsruher, Germany 20 Activité Physique, Sport et Santé, UR18JS01, Observatoire National du Sport, Tunis, Tunisie 21 Georgia Southern University, Statesboro, GA 30458, USA 22 PharmD, BCBS; PharmIAD, Inc,Savannah, GA, USA 23 Health and Social Services, Fundesalud, 06800, Merida, Spain

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NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.

24 The E-senior association, 75020 Paris, France 25 Department of Health Psychology, University Medical Center Groningen,University of Groningen,

Groningen, The Netherlands 26 Department of Medicine, Ulm University, Leimgrubenweg 14, 89075 Ulm, Germany 27 Department of Exercise Science, Yarmouk University, Irbid, Jordan 28 Department of Instruction and Supervision, The University of Jordan, Jordan 29 Digital Research Centre of Sfax, Sfax, Tunisia 30 Faculty of Psychology and Education Sciences, University of Porto, Porto Portugal 31 ISCTE-Instituto Universitário de Lisboa, Av. das Forças Armadas, 1649-026 Lisboa, Portugal 32 Institute for Kinesiology Research, Science and ResearchCentre, Koper, Slovenia 33 Centre for Bioengineering and Biotechnology University of Waterloo, Waterloo, Canda 34 School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK 35 Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology: Physical Activity, Health and

Learning (LINP2-2APS), UFR STAPS, UPL, Paris Nanterre University, 92000 Nanterre, France

Correspondant Author:

Dr. Achraf Ammar, Institute for Sports Science, Otto-von-Guericke University Magdeburg, Zschokkestraße

32, 39104 Magdeburg, Germany, Phone: +49 391 6757395, E-mail: ammar1.achraf@ovgu.de

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Effects of home confinement on mental health and lifestyle behaviours during the COVID-19

outbreak: Insight from the "ECLB-COVID19" multi countries survey

Abstract

Background

Although recognised as effective measures to curb the spread of the COVID-19 outbreak, social

distancing and self-isolation, have been suggested to generate burden throughout the population. To

provide scientific data to help identify risk-factors for the psychosocial strain during the COVID-19

outbreak, an international cross-disciplinary online survey was circulated in April 2020. This report

outlines the mental, emotional and behavioural consequences of COVID-19 home confinement.

Method

Thirty-five research organisations from four continents promoted the survey through their networks

to the general society, in Ten different languages. Questions were presented in a differential format

with questions related to responses “before” and “during” confinement period.

Results

1047 replies (54% women) from Western-Asia (36%), North-Africa (40%), Europe (21%) and other

countries (3%) were analysed. The COVID-19 home confinement evoked a negative effect on mental

wellbeing and emotional status (P < 0.001; 0.43 ≤ d ≤ 0.65) with a greater proportion of individuals

experiencing psychosocial and emotional disorders (10% to 16.5%). These psychosocial tolls were

associated with unhealthy lifestyle behaviours with a greater proportion of individuals experiencing

(i) physical (+15.2%) and social (71.2%) inactivity, (ii) poor sleep quality (12.8%), (iii) unhealthy

diet behaviours (10%), and (iv) unemployment (6%). Conversely, participants demonstrated a greater

use (15%) of technology solutions during the confinement period.

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Conclusion

These findings elucidate the risk of psychosocial strain during the current home confinement period

and provide a clear remit for the urgent implementation of technology-based intervention to foster an

Active and Healthy Confinement Lifestyle (AHCL).

Keywords: Public health; Pandemic; Mental wellbeing; Depression; Satisfaction, Behaviours.

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Introduction

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease caused by newly

discovered Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2).1 The disease was

first identified in December 2019 in Wuhan, the capital of China's Hubei province and has since

spread globally to affect around 3 million people (4th week of April 2020), including nearly 200,000

deaths in more than 220 countries.2 Due to the ever-growing number of confirmed cases and to avoid

overwhelming health systems, WHO and public health authorities around the world are acting to

contain the rapid spread of the COVID-19 outbreak, with primary measures focusing on social

distancing, self-isolation, and nationwide lockdowns.

Although recognized with hygiene care as one of the most effective measures to curb the

spread of disease, the weakening of social contact result in the devastating loss of leisure and working

hours, disruption of normal lifestyle, and generation of stress throughout the population (WHO,

2020b, Hossain, 2020).3,4 As a result, anxiety, frustration, panic attacks, loss or sudden increase of

appetite, insomnia, depression, mood-swings, delusions, fear, sleep disorders, and suicidal/ domestic-

violence cases have become quite common during lockdowns with helpline numbers being

overloaded through surges in SOS.5-8 Similarly, Brooks et al.9 reported several psychological issues

during quarantine periods in patients including: emotional and mood disturbance, numbness,

depression, irritability, stress, anger, nervousness, guilt, sadness, fear, vigilant handwashing and

avoidance of crowd (SARS, H1N1 influenza, Equine influenza and Ebola). During these periods of

and precautionary isolation, Purssell et al.10 and Sharma et al.11 reported negative psychological

effects (i.e., increased levels of anxiety and depression). Social impacts have also been reported,

including engendered limited visiting, lesser interaction with providers, and social exclusion.12

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Therefore, in such times of crisis, there exists an emergent need to support mental and

psychosocial well-being in target groups during outbreaks to minimize the psychosocial toll. In this

context, mental health initiatives focused on (i) educating public and health care workers on how to

properly deal with the immense pressure and anxiety, (ii) providing targeted mental health

surveillance followed by effective interventions for at-risk populations (e.g., patients with prior

mental health diagnosis, the elderly, people in total home confinement), and (iii) proactively

establishing mental health programs specifically designed to manage the pandemic’s aftermath, have

been recently suggested as urgent measures of preventive and early intervention (WHO, 2020b;

Galea et al. 2020, Usher et al. 2020).3,13,14 The psychosocial needs of at-risk individuals, including

those in quarantine and/or home confinement, are suggested to be unique.14 Preventive, early and

rehabilitation-focused interventions to promote mental wellbeing should be designed to be “crisis-

oriented” and should be informed by outcomes from scientific research, as opposed to hypothetical

and speculative suggestions. Consistent with this standpoint, a recent “paper advises” article

highlighted the urgent need of research to help improve understanding of the mental health

consequences of the COVID-19 pandemic on the public.15 Therefore, to provide scientific data to

help characterise the psychosocial effects of the COVID-19 crisis, our ECLB-COVID19 research

group recently launched a multiple-language and multi-country anonymous survey to assess the

effects of home confinement on psychosocial health status and multiple lifestyle behaviours during

the COVID-19 outbreak (ECLB-COVID19).

An accurate understanding of behavioural changes accompanying the COVID-19 lockdowns

is a necessary step toward a crisis-oriented based-research intervention to foster healthy lifestyle and

physical and mental wellbeing. Based on data extracted from the first thousand multi-country

responses (1047 participants), the present manuscript aims to provide insight into the effect of home-

confinement on mental wellbeing, depression, life satisfaction and multidimension lifestyle

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behaviours (i.e., social participation, physical activity, dietary behaviours, sleep quality and

technology-use). Additionally, we aimed at identifying possible relationships between psychosocial

and behavioural changes during the confinement period.

We hypothesize that social distancing would negatively affect mental and emotional wellbeing via

increases in sedentary activity, social exclusion, decreasing sleep quality and decreased adherence to

healthy diet.

There is a common method description in all ECLB-COVID19 papers.

Methods

We report findings on the first 1047 replies to an international online-survey on mental health and

multi-dimension lifestyle behaviours during home confinement (ECLB-COVID19). ECLB-

COVID19 was opened on April 1, 2020, tested by the project’s steering group for a period of 1 week,

before starting to spread it worldwide on April 6, 2020. Thirty-five research organizations from

Europe, North-Africa, Western Asia and the Americas promoted dissemination and administration of

the survey. ECLB-COVID19 was administered in English, German, French, Arabic, Spanish,

Portuguese, and Slovenian languages (currently provided also in Dutch, Persian and Italian). The

survey included sixty-four questions on health, mental wellbeing, mood, life satisfaction and

multidimension lifestyle behaviours (physical activity, diet, social participation, sleep, technology-

use, need of psychosocial support). All questions were presented in a differential format, to be

answered directly in sequence regarding “before” and “during” confinement conditions.

The study was conducted according to the Declaration of Helsinki. The protocol and the consent form

were fully approved (identification code: 62/20) by the Otto von Guericke University Ethics

Committee.

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Survey development and promotion

The ECLB-COVID19 electronic survey was designed by a steering group of multidisciplinary

scientists and academics (i.e., human science, sport science, neuropsychology and computer science)

at the University of Magdeburg (principal investigator), the University of Sfax, the University of

Münster and the University of Paris-Nanterre, following a structured review of the literature. The

survey was then reviewed and edited by Over 50 colleagues and experts worldwide. The survey was

uploaded and shared on the Google online survey platform. A link to the electronic survey was

distributed worldwide by consortium colleagues via a range of methods: invitation via e-mails, shared

in consortium’s faculties official pages, ResearchGate™, LinkedIn™ and other social media

platforms such as Facebook™, WhatsApp™ and Twitter™. Public were also involved in the

dissemination plans of our research through the promotion of the ECLB-COVID19 survey in their

networks. The survey included an introductory page describing the background and the aims of the

survey, the consortium, ethics information for participants and the option to choose one of seven

available languages (English, German, French, Arabic, Spanish, Portuguese, and Slovenian). The

present study focusses on the first thousand responses (i.e., 1047 participants), which were reached

on April 11, 2020, approximately one-week after the survey began. This survey was open for all

people worldwide aged 18 years or older. People with cognitive decline are excluded.

Data privacy and consent of participation

During the informed consent process, survey participants were assured all data would be used only

for research purposes. Participants’ answers are anonymous and confidential according to Google’s

privacy policy (https://policies.google.com/privacy?hl=en). Participants don’t have to mention their

names or contact information. In addition, participant can stop participating in the study and can leave

the questionnaire at any stage before the submission process and their responses will not be saved.

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Response will be saved only by clicking on “submit” button. By completing the survey, participants

are acknowledging the above approval form and are consenting to voluntarily participate in this

anonymous study. Participants have been requested to be honest in their responses.

Survey questionnaires

The ECLB-COVID19 is a multi-country electronic survey designed to assess change in multiple

lifestyle behaviours during the COVID-19 outbreak. Therefore, a collection of validated and/or crisis-

oriented briefs questionnaires were included. These questionnaires assess mental wellbeing (Short

Warwick-Edinburgh Mental Well-being Scale (SWEMWBS)),16 mood and feeling (Short Mood and

Feelings Questionnaire (SMFQ)),17 life satisfaction (Short Life Satisfaction Questionnaire for

Lockdowns (SLSQL), social participation (Short Social Participation Questionnaire for Lockdowns

(SSPQL)), physical activity (International Physical Activity Questionnaire Short Form (IPAQ-SF)),18

19 diet behaviours (Short Diet Behaviours Questionnaire for Lockdowns (SDBQL)), sleep quality

(Pittsburgh Sleep Quality Index (PSQI))20 and some key questions assessing the technology-use

behaviours (Short Technology-use Behaviours Questionnaire for Lockdowns (STBQL)),

demographic information and the need of psychosocial support. Reliability of the shortened and/or

newly adopted questionnaires was tested by the project steering group through piloting, prior to

survey administration. These brief crisis-oriented questionnaires showed good to excellent test-retest

reliability coefficients (r = 0.84-0.96). A multi-language validated version already existed for the

majority of these questionnaires and/or questions. However, for questionnaires that did not already

exist in multi-language versions, we followed the procedure of translation and backtranslation, with

an additional review for all language versions from the international scientists of our consortium.

Detailed descriptions of the aforementioned tools including total score calculation and interpretation

of each questionnaires are available as supplementary file 1. As a result, a total of 64 items were

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included in the ECLB-COVID19 online survey in a differential format. Each item or question

requested two answers, one regarding the period before and the other regarding the period during

confinement. Thus, participants were guided to compare the situations.

Given the large number of included questions and in order to give a multidimension overview of the

recorded change “during” compared to “before” the confinement period, the present paper focuses

only on the total scores of the included questionnaires, without detailed analysis regarding specific

changes in each questionnaire.

Data Analysis

Descriptive statistics were used to define the proportion of responses for each question and the

total distribution of the total score of each questionnaire. All statistical analyses were performed using

the commercial statistical software STATISTICA (StatSoft, Paris, France, version 10.0). Normality

of the data distribution was confirmed using the Shapiro-Wilks-W-test. Values were computed and

reported as mean ± SD (standard deviation). To assess significant difference in total scored responses

between “before” and “during” confinement period, Paired samples t-tests were used for normally

distributed data and the Wilcoxon test was used when normality was not assumed. Effect size

(Cohen’s d) was calculated to determine the magnitude of the change score and interpreted using the

following criteria: 0.2 (small), 0.5 (moderate), and 0.8 (large).21 Pearson product-moment correlation

tests were used to assess possible relationships between the “before-after” Δ of the assessed

multidimension total scores. Statistical significance was identified at p<0.05.

Results

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Sample description

1047 participants were included in the preliminary sample. Overall, 54% of the sample were women

and 46% were men. Geographical breakdowns were from Asian (36%, mostly from Western Asia),

African (40%, mostly from North Africa), European (21%) and other (3%) countries. Age, health

status, employment status, level of education, and marital status are presented in Table 1.

Mental wellbeing, depression, life satisfaction and need of psychosocial support

Change in the total score of the of the SWEMWBS, SMFQ, and SLSQL questionnaire and the

psychological support key question from “before” to “during” home confinement period are presented

in Figure 1. Statistical analysis showed a significant difference in all tested parameters (14.12≤ t ≤

21.05; P < 0.001, 0.43 ≤ d ≤ 0.65). Particularly, total score in mental wellbeing and life satisfaction

questionnaires decreased by 9.4% (t=18.82, p<0.001, d=0.58) and 16% (t=21.05, p<0.001, d=0.65),

respectively from “before” to “during” with more individuals (+12.89%) reporting a very low-low

mental wellbeing and more people feeling dissatisfied (extremely-slightly) (+16.5%) “during”

compared to “before” the confinement period. In contrast, total score in the depression monitoring

questionnaire, as well as in the need of psychosocial support question, increased by 44.9% (t=14.12,

p<0.001, d=0.43) and 20.2 % (t=14.83, p<0.001, d=0.56) from “before” to “during,” with more people

developing depressive symptoms/states (10%) and more people declaring a need (sometimes-all

rimes) of psychosocial support (16.1%) “during” compared to “before” the confinement period.

Social participation, physical activity, diet and sleep behaviours

Change in the total score of the of the SSPQL, IPAQ-SF, SDBQL, and PSQI questionnaires from

“before” to “during” home confinement period are presented in Figure 2. Statistical analysis showed

a significant difference between both periods in all tested parameters (10.66≤ t ≤ 69.16; P < 0.001,

0.3 ≤ d ≤ 2.14). Total score in social participation and physical activity (i.e., days/week of all physical

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activity) questionnaires decreased by 42% (t=69.19 p<0.001, d=2.14) and 24% (t=15.61, p<0.001,

d=0.482), respectively from “before” to “during,” There were more socially (+71.15%, Never-Rarely

socially active) and physically (+15.2, 0-1 days/week of all physical activity) inactive individuals

“during” compared to “before” the confinement period. In contrast, total score in the diet and sleep

monitoring questionnaires increased significantly by 4.4% (t=-10.66, p<0.001, d=0.50) and 12 %

(z=10.58, p<0.001, d=0.3) from “before” to “during” with more people experiencing poor sleep quality

(+12.8%) and more people classifying (most of the time-always) their diet behaviours as unhealthy

(10%) “during” compared to “before” the confinement period.

Short Technology-use Lockdowns Questionnaire

Change in technology-use score from “before” to “during” confinement period in response to SLSQL

are presented in Figure 3. Statistical analysis showed the total score of the technology-use behaviour

increased significantly (8.8%) at “during” compared to “before” home confinement (t=14.01,

P<0.001, d=0.43). Particularly, scores related to the use of internet/social media for communication

significantly increased “during” compared to “before” the confinement period t=17.03, P<0.001 and

d=0.54. Similarly, higher scores related to the use of technology-based tools for physical activity was

registered during the confinement period (t=9.03, p<0.001, d=0.28). However, no significant change

was recorded for scores related to the use of technology-based tools for dietary purposes (t=0.61,

p=0.53, d=0.01).

Relationship between change in mental and emotional wellbeing and behavioural factors

Table 2 shows the relationship between the change “before-after” of the assessed variables. As this

table indicates, the mental and emotional related variables were significantly correlated to the

majorities of lifestyle behaviours (0.01 ≤ P ≤ 0.001 and 0.1 ≤ r ≤ 0.41). Particularly, Δ in total score

of mood and feeling questionnaires showed significant correlations to all behavioural changes with

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positive correlation to the diet and sleep behaviours (p<0.001, 0.3 ≤ r ≤ 0.41) and negative correlation

to social participation and physical activity (p<0.001, -0.25 ≤ r≤ -0.14). Inversely, Δ in total score of

mental wellbeing and life satisfaction were positive correlated to social participation (p<0.001, 0.23

≤ r≤ 0.28) and physical activity (p<0.01, 0.10 ≤ r≤ 0.15) and negatively correlated to the diet (p<0.001,

-0.21 ≤ r ≤ -0.14) and sleep behaviours (p<0.001, -0.32 ≤ r ≤ -0.23).

Discussion

The present study reports preliminary results from our first 1047 participants (54% female) who

responded to our ECLB-COVID19 multiple languages online survey. Preliminary findings from this

survey showed COVID-19 home confinement has a negative effect on mental wellbeing and

emotional status with more individuals (i) perceiving low mental wellbeing (+12.89%), (ii) feeling

dissatisfied (+16.5%), (iii) developing depression (+10%), and (iv) declaring a need of psychosocial

support (+16.1%) compared to “before” the confinement period. During similar pandemic crises

(2002–2004 SARS outbreak), previous research revealed several negative effects of quarantine

measures on mental health and were associated with psychological and emotional problems such as

depression and anxiety.22, 23 These negative effects (i.e., increased levels of anxiety and depression)

have also been reported in two recent systematic reviews and meta-analyses conducted by Purssell et

al.10 and Sharma et al.11 assessing the impact of isolation precaution on quality of life. Similarly, in

their recent review of the evidence, Brooks et al.9 reported several psychological perturbations and

emotional/ mood disturbances such as numbness, depression, irritability, stress, anger, nervousness,

guilt, sadness, fear, vigilant handwashing, and avoidance of crowds in infected patients (SARS,

MERS, H1N1 influenza, Ebola, and Equine influenza) during quarantine periods. Similarly, results

from Chinese studies indicate the COVID-19 outbreak engendered anxiety, depression, sleep

problems, and other psychological problems.7, 8 This is related to the coupling of psychomental well-

being to regular physical activity and to the related effects on immune function.24 With significant

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negative effects of the current COVID-19 pandemic on mental wellbeing, life satisfaction, and

depression scores of 1047 participants from different continents, the present findings support these

suggestions and elucidate the risk of mental disorders (e.g. low wellbeing, dissatisfaction and

depression) during the current home confinement period.

The resultant weakening of social contact with the disruption of normal lifestyles during the COVID-

19 outbreaks, have been recently suggested to generate stress throughout the population and thereby

to engender lower mental and emotional wellbeing (WHO, 2020b, Gammon and Hunt, 2018).3, 12 To

provide scientific evidence and deeper the understanding for these suggestions, the present multi-

dimension survey also focused on the lifestyle behavioural changes during the COVID-19 outbreak.

Main findings showed the negative psycho-emotional effect of COVID-19 home confinement was

accompanied with a negative effect on the majority of assessed lifestyle behaviours with more (i)

physically inactive peoples (+15.2), (ii) socially isolated peoples (+71.15%), (iii) unemployed

peoples (+6%), (iv) more peoples experiencing poor sleep quality (+12.8%), and (v) unhealthy diet

behaviours (+10%) compared to “before” the confinement period. Likewise, there are increased

number of peoples (+15%) who are “All times” using technology.

These preliminary findings confirm our hypotheses related to the lifestyle behaviours. To better

understand the behavioural changes recognized as risk factors of declined psychosocial wellbeing

during the confinement period, a correlation analysis between the Δ change in total scores of all

assessed variables from “before” to “during” confinement was performed. Main findings indicate

changes in mental wellbeing, mood and feeling and life satisfaction were significantly correlated to

changes in lifestyle behaviours, including social participation, physical activity, diet, and sleep. These

results suggest low mental wellbeing and life dissatisfaction and high level of depressive symptoms

are related to social isolation, sedentary lifestyle, unhealthy diet behaviour and poor sleep quality.

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Therefore, in order to mitigate the negative physical and psychosocial effects of home confinement,

an implementation of a multi-dimension “need-oriented” intervention is warranted. This intervention

should focus on enhancing social participation and promoting physical activity (e.g., the German

example: allowing people to do outdoor physical activity in the large public garden with respecting

distancing and hygiene precautions), healthy food, and sleep quality.

Since participants demonstrated a higher acceptance rate (21.8% vs. 36.8%) toward the use of

technology solutions, it seems interesting to foster social communication, and physical and mental

wellbeing through technology facilities (e.g., social platform, gamification, mhealth, interactive coach

etc.). Indeed, such ICT-based solutions would facilitate the delivery of COVID19-related health

services, as well as preventive and rehabilitation crisis-oriented intervention in the communities with

a specific challenge to reach risk populations.

To expand the target group, WHO and the national authorities are encouraged to implement, during

lockdowns crises, a “Technology-use” support system including factors such as reducing internet fee,

providing free based-ICT social inclusion platforms, promoting Gamification, Communication and

interactive coaching technologies, tracking contacts and symptoms, switching from 4G to 5G

network, to name a few.

Strengths and limitations

This is the first interdisciplinary international research project evaluating the psychosocial and

behavioural changes “during” compared to “before” the home confinement period using a multiple-

languages online survey. Preliminary findings from this study offers some important insights into

the effect of home confinement on mental wellbeing, emotional health status and the associated

multidimension behavioural change in response to the COVID-19 outbreak. However, given that data

of the present study has been collected from a heterogeneous population with no criteria-based

subsamples analysis, the present findings need to be interpreted with caution. Additionally, since the

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ECLB-COVID19 survey is still open and meanwhile also available in Dutch, Persian and Italian

languages, future post-hoc studies in a more representative sample will be conducted to assess the

interaction between the psychosocial strain evoked by COVID-19 and the geographical,

demographical, cultural and health characteristics of the participants.

Conclusion

The preliminary results of the survey reveal a considerable burden for mental wellbeing combined

with an unhealthy lifestyle during, compared to before, the confinement enforced by the COVID-19

pandemic. In particular, social and physical inactivity, an unhealthy diet and poor sleep quality were

associated with lower mental and emotional wellbeing (i.e., depressive and dissatisfaction feelings)

were triggered by the enforced home confinement. These multidimensional negative effects

underscore the importance to stakeholders and policy makers to develop, implement and publicise

interdisciplinary interventions to mitigate the physical and psychosocial strain evoked by this

pandemic. Promoting wellbeing by encouraging individuals to engage in indoor and/or outdoor

physical activity in large public parks, whilst conforming with distancing and hygiene

recommendations, can be suggested as preliminary measure with evidence for physical and mental

benefits. Moreover, since participants have demonstrated a higher acceptance of the use of technology

solutions during the confinement period, fostering an Active and Healthy Confinement Lifestyle

(AHCL) via an ICT-based approach can be implemented.

A proposed psychosocial strain mitigation strategy from ECLB-COVID19 consortium can be found

in the supplementary file 2.

Acknowledgement

We thank our consortium’s colleagues who provided insight and expertise that greatly assisted the

research. We thank all colleagues and peoples who believed on this initiative and helped to distribute

the anonymous survey worldwide. We are also immensely grateful to all participants who #StayHome

& #BoostResearch by voluntarily taken the #ECLB-COVID19 survey.

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Competing interest statement

All authors declare: no support from any organisation for the submitted work; no financial

relationships with any organisations that might have an interest in the submitted work in the previous

three years, no other relationships or activities that could appear to have influenced the submitted

work.

Details of funding

Research are urgently needed to help understand the mental health consequences of the covid-19

pandemic. However, normal funding mechanism to support scientific research are too slow. The

author received no specific funding for this work.

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Table 1: Demographic characteristics of the participants (N = 1047)

Variables N (%)

Gender

Male 484 (46.2%) Female 563 (53.8%)

Continent

North Africa 419 (40%) Western Asia 377 (36%) Europe 220 (21%) Other 31 (3%)

Age

18-35 577 (55.1%) 36-55 367 (35.1%) >55 103 (9.8%)

Level of Education

Master/doctorate degree 527 (50.3%) Bachelor’s degree 397 (37.9%) Professional degree 28 (2.7%)

High school graduate, diploma or the

equivalent 69 (6.6%)

No schooling completed 26 (2.5%)

Marital status

Single 455 (43.5%) Married/Living as couple 562 (53.7%) Widowed/Divorced/Separated 30 (2.9%)

Employment status

Employed for wages 538 (51.4%) Self-employed 74 (7.1%) Out of work/Unemployed 75 (7.2%) A student 259 (24.7%) Retired 23 (2.2%) Unable to work 9 (0.9%) Problem caused by COVID-19 59 (5.6%) Other 10 (1%)

Health state

Healthy 956 (91.3%)

With risk factors for cardiovascular

disease 81 (7.7%)

With cardiovascular disease 10 (1%)

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Table 2: Relationship between delta total score in mental wellbeing, mood and feeling, life satisfaction and the

multidimension lifestyle behaviours (social participation, physical activity, diet and sleep)

Mental

well

being

Mood and

feeling

Life

satisfaction

Need of

psychosocial

support

Social

participation

Physical

activity

Diet

behaviour

Sleep

behaviour

Mental well being 1

Mood and feeling -0.64*** 1

Life satisfaction 0.51*** -0.42*** 1

Need of psychosocial support -0.38*** 0.45*** -0.28*** 1

Social participation 0.28*** -0.25*** 0.23*** -0.13*** 1

Physical activity 0.15*** -0.14*** 0.10** -0.15*** 0.15*** 1

Diet behaviour -0.21*** 0.30*** -0.14*** 0.17*** -0.06 -0.18*** 1

Sleep behaviour -0.32*** 0.41*** -0.23*** 0.26*** -0.12*** -0.17*** 0.28*** 1

**: p<0.01; ***: p<0.001

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Figure 1: Response to the psychological support key question and total score of the mental wellbeing, mood and feelings, and short life

satisfaction questionnaires before and during home confinement.

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Figure 2: Total score of the social participation, physical activity, diet and sleep behaviors questionnaires before and during home

confinement.

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Figure 3: Responses to the Short Technology-use Lockdowns Questionnaire before and during home confinement.

Values were computed and reported as mean ± SEM (standard error of the mean).

*Significantly different from before confinement at p<0.05.

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